SoroushVahidi/scidocs huggingface dataset:
Arabic Tokenization, Part-of-Speech Tagging and Morphological Disambiguation in One Fell Swoop
(2005)

We present an approach to using a morphological analyzer for tokenizing and morphologically tagging (including partof-speech tagging) Arabic words in one process. We learn classifiers for individual morphological features, as well as ways of using these classifiers to choose among entries from the output of the analyzer. We obtain accuracy rates on all tasks in the high nineties.
The curvelet transform for fusion of very-high resolution multi-spectral and panchromatic images
(2006)

This paper presents a novel image fusion method, suitable for pan-sharpening of multispectral (MS) bands, based on multi-resolution analysis (MRA). The low-resolution MS bands are sharpened by injecting high-pass directional details extracted from the high-resolution panchromatic (Pan) image by means of the curvelet transform, which is a non-separable MRA, whose basis function are directional edges with progressively increasing resolution. The advantage with respect to conventional separable MRA, either decimated or not, is twofold: directional detail coefficients matching image edges may be preliminarily soft-thresholded to achieve denoising better than in the separable wavelet domain; modeling of the relationships between high-resolution detail coefficients of MS bands and of the Pan image is more fitting, being carried out in a directional wavelet domain. Experiments carried out on a very-high resolution MS + Pan QuickBird image show that the proposed curvelet method quantitatively outperforms state-of-the art image fusion methods, in terms of geometric, radiometric, and spectral fidelity.
Motivation and Second Language Acquisition 1
(2007)

This paper posits four stages of language acquisition, identified as elemental, consolidation, conscious expression, and automaticity and thought, and considers the role of motivation in this process. It distinguishes between two types of motivation, language learning motivation and classroom motivation, indicating how these relate to two distinct contexts, the cultural and the educational through their influence on integrativeness and attitudes toward the learning situation. It discusses how the two types of motivation are differentially involved in the four stages, and empirical support for this perspective is presented in the form of path analyses of two samples of students from Catalonia.
Leveraging Augmented Reality Training Tool for Medical Education: a Case Study in Central Venous Catheterization
(2018)

Central venous catheterization is a relatively common bedside medical procedure that involves the placement of a catheter into a patient»s internal jugular vein in order to administer medication or fluids. To learn this technique, medical students traditionally practice on training mannequins under the guidance of a clinical instructor. The objective of this project was to co-develop a standardized augmented reality solution for teaching medical students this procedure, which would enable them to practice independently and at their own pace. Following an iterative design and prototyping process, we compiled a comprehensive set of usability heuristics specific to augmented reality healthcare applications, used to identify unique usability issues associated with augmented reality software. This approach offers a better strategy to improve the usability of augmented reality system and increases the potential to standardize and render medical education more accessible. The benefits of applying augmented reality to simulated medical education come with heavy consequences in the event of poor learning outcomes. The usability of these systems is paramount to ensure the development of clinical competence is facilitated and not hindered.
Manipulator state estimation with low cost accelerometers and gyroscopes
(2012)

Robot manipulator designs are increasingly focused on low cost approaches, especially those envisioned for use in unstructured environments such as households, office spaces and hazardous environments. The cost of angular sensors varies based on the precision offered. For tasks in these environments, millimeter order manipulation errors are unlikely to cause drastic reduction in performance. In this paper, estimates the joint angles of a manipulator using low cost triaxial accelerometers by taking the difference between consecutive acceleration vectors. The accelerometer-based angle is compensated with a uniaxial gyroscope using a complementary filter to give robust measurements. Three compensation strategies are compared: complementary filter, time varying complementary filter, and extended Kalman filter. This sensor setup can also accurately track the joint angle even when the joint axis is parallel to gravity and the accelerometer data does not provide useful information. In order to analyze this strategy, accelerometers and gyroscopes were mounted on one arm of a PR2 robot. The arm was manually moved smoothly through different trajectories in its workspace while the joint angle readings from the on-board optical encoders were compared against the joint angle estimates from the accelerometers and gyroscopes. The low cost angle estimation strategy has a mean error 1.3° over the three joints estimated, resulting in mean end effector position errors of 6.1 mm or less. This system provides an effective angular measurement as an alternative to high precision encoders in low cost manipulators and as redundant measurements for safety in other manipulators.
Agents of Things (AoT): An intelligent operational concept of the Internet of Things (IoT)
(2013)

In this conceptual paper, we review the definitions, characteristics, and architecture of the Internet of Things (IoT) concept. We then identify the deficiencies of the IoT concept, analyze them, and discover the issue of lack of reasoning and intelligence in the IoT concept. We propose a solution to augment the IoT with intelligent software agents resulting in a new concept called the Agents of Things (AoT). The paper presents the AoT architecture and a scenario for one application of the proposed concept. Finally, it discusses the benefits of implementing AoT concept to solve real world issues and the future work.
Natural history and evolutionary principles of gene duplication in fungi
(2007)

Gene duplication and loss is a powerful source of functional innovation. However, the general principles that govern this process are still largely unknown. With the growing number of sequenced genomes, it is now possible to examine these events in a comprehensive and unbiased manner. Here, we develop a procedure that resolves the evolutionary history of all genes in a large group of species. We apply our procedure to seventeen fungal genomes to create a genome-wide catalogue of gene trees that determine precise orthology and paralogy relations across these species. We show that gene duplication and loss is highly constrained by the functional properties and interacting partners of genes. In particular, stress-related genes exhibit many duplications and losses, whereas growth-related genes show selection against such changes. Whole-genome duplication circumvents this constraint and relaxes the dichotomy, resulting in an expanded functional scope of gene duplication. By characterizing the functional fate of duplicate genes we show that duplicated genes rarely diverge with respect to biochemical function, but typically diverge with respect to regulatory control. Surprisingly, paralogous modules of genes rarely arise, even after whole-genome duplication. Rather, gene duplication may drive the modularization of functional networks through specialization, thereby disentangling cellular systems.
Implementation of potential field method for mobile robot navigation in greenhouse environment with WSN support
(2010)

This paper deals with the implementation of mobile measuring station in greenhouse environment navigated using potential field method. The function of a greenhouse is to create the optimal growing conditions for the full life of the plants. Using autonomous measuring systems helps to monitor all the necessary parameters for creating the optimal environment in the greenhouse. The robot equipped with sensors is capable of driving to the end and back along crop rows inside the greenhouse. It introduces a wireless sensor network that was used for the purpose of measuring and controlling the greenhouse application. Continuous advancements in wireless technology and miniaturization have made the deployment of sensor networks to monitor various aspects of the environment increasingly flexible.
Automatic common-centroid layout generation for binary-weighted capacitors in charge-scaling DAC
(2012)

As the precision of the capacitance ratios among binary-weighted capacitors is the key to accuracy/performance of charge-scaling digital-to-analog converters, it is very important to generate a highly matched common-centroid layout with minimum routing-induced parasitics. However, most of the previous works only focused on common-centroid placement optimization with the consideration of random and systematic mismatch. This paper introduces a novel common-centroid capacitor layout generation approach to minimize the parasitic impact on circuit accuracy/performance. Experimental results show that, compared with the manual layout, the layout generated by the presented approach can achieve even smaller layout area and better circuit accuracy/performance within much shorter time.
Scaffolds in tissue engineering bone and cartilage.
(2000)

Musculoskeletal tissue, bone and cartilage are under extensive investigation in tissue engineering research. A number of biodegradable and bioresorbable materials, as well as scaffold designs, have been experimentally and/or clinically studied. Ideally, a scaffold should have the following characteristics: (i) three-dimensional and highly porous with an interconnected pore network for cell growth and flow transport of nutrients and metabolic waste; (ii) biocompatible and bioresorbable with a controllable degradation and resorption rate to match cell/tissue growth in vitro and/or in vivo; (iii) suitable surface chemistry for cell attachment, proliferation, and differentiation and (iv) mechanical properties to match those of the tissues at the site of implantation. This paper reviews research on the tissue engineering of bone and cartilage from the polymeric scaffold point of view.
3D Ego-Pose Estimation via Imitation Learning
(2018)

Ego-pose estimation, i.e., estimating a person’s 3D pose with a single wearable camera, has many potential applications in activity monitoring. For these applications, both accurate and physically plausible estimates are desired, with the latter often overlooked by existing work. Traditional computer vision-based approaches using temporal smoothing only take into account the kinematics of the motion without considering the physics that underlies the dynamics of motion, which leads to pose estimates that are physically invalid. Motivated by this, we propose a novel control-based approach to model human motion with physics simulation and use imitation learning to learn a videoconditioned control policy for ego-pose estimation. Our imitation learning framework allows us to perform domain adaption to transfer our policy trained on simulation data to real-world data. Our experiments with real egocentric videos show that our method can estimate both accurate and physically plausible 3D ego-pose sequences without observing the cameras wearer’s body.
Jointless structure and under-actuation mechanism for compact hand exoskeleton
(2011)

It is important for a wearable robot to be compact and sufficiently light for use as an assistive device. Since human fingers are arranged in a row in dense space, the concept of traditional wearable robots using a rigid frame and a pin joint result in size and complexity problems. A structure without a conventional pin joint, called a jointless structure, has the potential to be used as a wearable robotic hand because the human skeleton and joint can replace the robot's conventional structure. Another way to reduce the weight of the system is to use under-actuation. Under-actuation enables adaptive grasping with less number of actuators for robotic hands. Differential mechanisms are widely used for multi-finger under-actuation; however, they require additional working space. We propose a design with a jointless structure and a novel under-actuation mechanism to reduce the size and weight of a hand exoskeleton. Using these concepts, we developed a prototype that weighs only 80 grams. To evaluate the prototype, fingertip force and blocked force are measured. Fingertip force is the force that can be applied by the finger of the hand exoskeleton on the object surface. The fingertip force is about 18 N when actuated by a tension force of 35 N from the motor. 18 N is sufficient for simple pinch motion in daily activities. Another factor related to performance of the under-actuation mechanism is blocked force, which is a force required to stop one finger while the other finger keeps on moving. It is measured to be 0.5 N, which is sufficiently small. With these experiments, the feasibility of the new hand exoskeleton has been shown.
Multiband Handset Antenna Combining a PIFA, Slots, and Ground Plane Modes
(2009)

A multiband handset antenna combining a PIFA and multiple slots on a ground plane is presented. It is shown by means of simulations that the slots on the ground plane have a double function: to tune the ground plane resonance at low frequencies (f ¿ 900 MHz) and to act as parasitic radiators at high frequencies (f ¿ 1800 MHz). A prototype is designed and built featuring a behavior suitable for low frequencies (GSM850 and GSM900) and for high frequencies spanning from DCS1800 to Bluetooth, and including, for instance, PCS1900, UMTS2000, and other possible systems. Reflection coefficient, efficiency, and radiation patterns are measured and compared with a design without slots to prove the advantages of the slotted ground plane. The component effect is investigated to determine critical areas where the placement is not recommended. Besides, the effect of the slot of the ground plane on SAR is investigated, by discussing the effect of the ground plane and slot modes for two phone positions. The total antenna volume of the proposed design is 40 × 15 × 6 mm3.
3D Face Recognition Using Shapes of Facial Curves
(2006)

Recognition of human beings using shapes of their full facial surfaces is a difficult problem. Our approach is to approximate a facial surface using a collection of (closed) facial curves, and to compare surfaces by comparing their corresponding curves. The differences between shapes of curves are quantified using lengths of geodesic paths between them on a pre-defined curve shape space. The metric for comparing facial surfaces is a composition of the metric involving individual facial curves. These ideas are demonstrated in the context of face recognition using the nearest-neighbor classifier
CSRR loaded Sierpinski gasket fractal antenna for multiband applications
(2016)

The CSRR loaded Sierpinski fractal antenna for multiband applications are presented. This model fairs that the multiband presence of the Sierpinski fractal antenna is a fallout of its fractal nature. The antenna consists of iterations of sierpinski gasket with a complementary split ring resonator. In plan to provoke multi resonant frequency band aspect, these CSRR are implanted back side of the substrate. The simulated results offers a three operating bands, covering C band at 5.72 GHz, Ku band at 14.3 GHz and 16.06 GHz. The size of the CSRR loaded Gasket antenna is 14 mm × 12 mm × 1.6 mm3 printed on FR4 substrate. The parametric review and simulated radiation component are presented.
A Lie Never Lives to be Old: The Effects of Fake Social Information on Consumer Decision-Making in Crowdfunding
(2015)

The growing success of social media led to a strong presence of social information such as customer product reviews and product ratings in electronic markets. While this information helps consumers to better assess the quality of goods before purchase, its impact on consumer decision-making also incentivizes sellers to game the system by creating fake data in favor of specific goods in order to deliberately mislead consumers. As a consequence, consumers could make suboptimal choices or could choose to disregard social information altogether. In this exploratory study, we assess the effects nongenuine social information has on the consumer’s decision-making in the context of reward-based crowdfunding. Specifically, we capture unnatural peaks in the number of Facebook Likes that a specific crowdfunding campaign receives on the platforms Kickstarter and Indiegogo and observe subsequent campaign performance. Our results show that fake Facebook Likes have a very short-term positive effect on the number of backers participating in the respective crowdfunding campaign. However, this peak in participation is then followed by a period in which participation is lower than prior to the existence of the non-genuine social information. We further discuss circumstances that foster this artificial manipulation of quality signals.
Opening black box Data Mining models using Sensitivity Analysis
(2011)

There are several supervised learning Data Mining (DM) methods, such as Neural Networks (NN), Support Vector Machines (SVM) and ensembles, that often attain high quality predictions, although the obtained models are difficult to interpret by humans. In this paper, we open these black box DM models by using a novel visualization approach that is based on a Sensitivity Analysis (SA) method. In particular, we propose a Global SA (GSA), which extends the applicability of previous SA methods (e.g. to classification tasks), and several visualization techniques (e.g. variable effect characteristic curve), for assessing input relevance and effects on the model's responses. We show the GSA capabilities by conducting several experiments, using a NN ensemble and SVM model, in both synthetic and real-world datasets.
Learning to predict slip for ground robots
(2006)

In this paper we predict the amount of slip an exploration rover would experience using stereo imagery by learning from previous examples of traversing similar terrain. To do that, the information of terrain appearance and geometry regarding some location is correlated to the slip measured by the rover while this location is being traversed. This relationship is learned from previous experience, so slip can be predicted later at a distance from visual information only. The advantages of the approach are: 1) learning from examples allows the system to adapt to unknown terrains rather than using fixed heuristics or predefined rules; 2) the feedback about the observed slip is received from the vehicle's own sensors which can fully automate the process; 3) learning slip from previous experience can replace complex mechanical modeling of vehicle or terrain, which is time consuming and not necessarily feasible. Predicting slip is motivated by the need to assess the risk of getting trapped before entering a particular terrain. For example, a planning algorithm can utilize slip information by taking into consideration that a slippery terrain is costly or hazardous to traverse. A generic nonlinear regression framework is proposed in which the terrain type is determined from appearance and then a nonlinear model of slip is learned for a particular terrain type. In this paper we focus only on the latter problem and provide slip learning and prediction results for terrain types, such as soil, sand, gravel, and asphalt. The slip prediction error achieved is about 15% which is comparable to the measurement errors for slip itself
Bartender: a fast and accurate clustering algorithm to count barcode reads
(2018)

Motivation
Barcode sequencing (bar-seq) is a high-throughput, and cost effective method to assay large numbers of cell lineages or genotypes in complex cell pools. Because of its advantages, applications for bar-seq are quickly growing-from using neutral random barcodes to study the evolution of microbes or cancer, to using pseudo-barcodes, such as shRNAs or sgRNAs to simultaneously screen large numbers of cell perturbations. However, the computational pipelines for bar-seq clustering are not well developed. Available methods often yield a high frequency of under-clustering artifacts that result in spurious barcodes, or over-clustering artifacts that group distinct barcodes together. Here, we developed Bartender, an accurate clustering algorithm to detect barcodes and their abundances from raw next-generation sequencing data.


Results
In contrast with existing methods that cluster based on sequence similarity alone, Bartender uses a modified two-sample proportion test that also considers cluster size. This modification results in higher accuracy and lower rates of under- and over-clustering artifacts. Additionally, Bartender includes unique molecular identifier handling and a 'multiple time point' mode that matches barcode clusters between different clustering runs for seamless handling of time course data. Bartender is a set of simple-to-use command line tools that can be performed on a laptop at comparable run times to existing methods.


Availability and implementation
Bartender is available at no charge for non-commercial use at https://github.com/LaoZZZZZ/bartender-1.1.


Contact
sasha.levy@stonybrook.edu or song.wu@stonybrook.edu.


Supplementary information
Supplementary data are available at Bioinformatics online.
The comparation of text mining with Naive Bayes classifier, nearest neighbor, and decision tree to detect Indonesian swear words on Twitter
(2017)

Twitter is one of world most famous social media. There are many statement expresed in Twitter like happiness, sadness, public information, etc. Unfortunately, people may got angry to each other and write it down as a tweet on Twitter. Some tweet may contain Indonesian swear words. It's serious problem because many Indonesians may not tolerated swear words. Some Indonesian swear words may have multiple means, not always an Indonesian swear word means insulting. Twitter has provide tweet's data by account, trending topics, and advance keyword. This work try to analyze many tweet about political news, political event, and some Indonesian famous person because the tweet assumed contains many Indonesian swear word. The derived tweets will process in text mining and then analyzed by classification process using Naive Bayes Classifier, Nearest Neighbor, and Decision Tree to detect Indonesian swear word. This work expected to discover the high accurate classification model. It means, the model can differentiate the real meaning of Indonesian swear word contained in tweet.
Bayesian Symbol-Refined Tree Substitution Grammars for Syntactic Parsing
(2012)

We propose Symbol-Refined Tree Substitution Grammars (SR-TSGs) for syntactic parsing. An SR-TSG is an extension of the conventional TSG model where each nonterminal symbol can be refined (subcategorized) to fit the training data. We aim to provide a unified model where TSG rules and symbol refinement are learned from training data in a fully automatic and consistent fashion. We present a novel probabilistic SR-TSG model based on the hierarchical Pitman-Yor Process to encode backoff smoothing from a fine-grained SR-TSG to simpler CFG rules, and develop an efficient training method based on Markov Chain Monte Carlo (MCMC) sampling. Our SR-TSG parser achieves an F1 score of 92.4% in the Wall Street Journal (WSJ) English Penn Treebank parsing task, which is a 7.7 point improvement over a conventional Bayesian TSG parser, and better than state-of-the-art discriminative reranking parsers.